Air-sea fluxes of CO2 and CH4 from the Penlee Point Atmospheric Observatory on the south-west coast of the UK

We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights ≥18ma.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable (≤ ±20% in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20±3; 38±3; 29±6 μmolem-2 d-1 at 15, 18, 27ma.m.s.l.) than during falling tides (14±2; 22±2; 21±5 μmolem-2 d-1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 μmolem-2 d-1 over hourly timescales (4 μmolem-2 d-1 over 24 h).

Air-sea fluxes of CO2 and CH4 from the Penlee Point Atmospheric Observatory on the south-west coast of the UK

We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights ≥18ma.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable (≤ ±20% in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20±3; 38±3; 29±6 μmolem-2 d-1 at 15, 18, 27ma.m.s.l.) than during falling tides (14±2; 22±2; 21±5 μmolem-2 d-1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 μmolem-2 d-1 over hourly timescales (4 μmolem-2 d-1 over 24 h).

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

Using multifractals to evaluate oceanographic model skill

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.